MEDEIROS, V. M. C.; http://lattes.cnpq.br/3406650923331951; MEDEIROS, Viviane Micaela Canuto.
Resumen:
The Stenolepis ridleyi and Colobosauroides cearenses lizards belong to the family
Gymnophtalmidae, composed of lizards known as microteiids. Both species have a distribution
restricted to the Northeast portion above the São Francisco River, but are still little understood.
Thus, the distribution pattern of these two species was investigated using the ecological niche
modeling tool. The occurrence data were obtained in the literature and in herpetological
collections and the environmental variables collected in the online database, AMBDATA. The
potential distribution was estimated using the Maxent algorithm and the map was made using
the QGIS 3.4.1 software. For S. ridleyi, 20 records were obtained, for the locations of
Pernambuco, Paraíba, Ceará and Alagoas and the calculated model estimated as potential areas
the region of Piauí, Center-North Piauí, Bahia, Chapada Diamantina region, Rio Grande do
Norte in the regions of Seridó Potiguar and Alto Oeste. For C. cearenses 18 records were
obtained, for the locations of Ceará and Paraíba and the calculated model estimated as potential
areas the Northern region of the state of Maranhão, Pernambuco, Rio Grande do Norte and a
region in the state of Bahia, above the São Francisco River. The AUC values of the distribution
model of the two species showed significant values, 0.996 (S. ridleyi) and 0.998 (C. cearenses),
indicating that both models are reliable in predicting their distributions. The distribution pattern
found for S. ridleyi is similar to that of the genus Acratosaura, its brother group, being related
to Brejos de Altitude, which can be understood and explained by the theory of niche
conservatism. On the other hand, C. cearenses presented a distribution pattern similar to that of
the brother group Dryadosaura nordestina and Anatosaura, being found in Brejos de Altitude
and in caatinga areas, however, its proposed potential areas should be investigated in future
sampling works, because despite the high probability of occurrence proposed by the model, the
species may not be present in these environments, due to geographical barriers.